Separation of space group targets based on high-order moment function and EMD

Ying Luo, Yi-jun Chen, Hua Guan, Tao-yong Li, D. Deng
{"title":"Separation of space group targets based on high-order moment function and EMD","authors":"Ying Luo, Yi-jun Chen, Hua Guan, Tao-yong Li, D. Deng","doi":"10.1109/RADAR.2014.7060269","DOIUrl":null,"url":null,"abstract":"Space target recognition is one of the radar's significant tasks. The separation of group targets is the basis of the target recognition when several targets are within a range cell of one radar beam. In this paper, a method for group targets separation based on high-order moment function and empirical model decomposition (EMD) is proposed. The first step is deriving the high-order moment function of the target echo signal, and then processing the imaginary parts of the high-order moment function with EMD method. We can achieve the separation of group targets according to the derivational IMF from the decomposition. Simulation is given to validate the effectiveness of the proposed method.","PeriodicalId":317910,"journal":{"name":"2014 International Radar Conference","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 International Radar Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RADAR.2014.7060269","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Space target recognition is one of the radar's significant tasks. The separation of group targets is the basis of the target recognition when several targets are within a range cell of one radar beam. In this paper, a method for group targets separation based on high-order moment function and empirical model decomposition (EMD) is proposed. The first step is deriving the high-order moment function of the target echo signal, and then processing the imaginary parts of the high-order moment function with EMD method. We can achieve the separation of group targets according to the derivational IMF from the decomposition. Simulation is given to validate the effectiveness of the proposed method.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于高阶矩函数和EMD的空间群目标分离
空间目标识别是雷达的重要任务之一。当多个目标在同一雷达波束的距离单元内时,群目标分离是目标识别的基础。提出了一种基于高阶矩函数和经验模型分解(EMD)的群目标分离方法。首先推导目标回波信号的高阶矩函数,然后用EMD方法对高阶矩函数的虚部进行处理。我们可以根据分解得到的衍生IMF来实现群目标的分离。仿真结果验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
A real-time high resolution passive WiFi Doppler-radar and its applications Multi-sensor full-polarimetric SAR Automatic Target Recognition using pseudo-Zernike moments Evaluation of the attenuation in L-band due to the foliage in function of the elevation angle Cognitive kriging metamodels for forest characterization and target detection Development of a planetary georadar prototype with agile beam (AGILE)
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1